As the end of the calendar year approaches, the inevitable articles and conversations about forecasting arise. We are asked for our forecasts and we provide a number. Perhaps that’s at the beginning of the quarter, and we are held accountable for that number through the remainder of the quarter—though that number always changes, and rarely is it an upward change.
But the forecast isn’t a number!
The forecast is really about a deal. Will a decision be made, and a PO signed in a specific timeframe–say this quarter? The forecast becomes the aggregation of the deals we believe will be completed in the quarter. If we want high forecast integrity and accuracy, the only way we do this is on how we manage each deal that we have committed to the forecast.
Now, that we have identified the forecast is really about a deal, or a collection of deals, how do we increase the accuracy of those forecasts? How do we “make the number?”
It’s really about sharpening our deal strategies and execution.
Too often, we commit something to the forecast based on where it is positioned in our pipeline. Our CRM systems all come with stage probabilities. In prospecting, we have a very low probability assigned. As it moves through qualifying, discovery, proposing, closing, the probability increases. And our forecasts become the weighted average of the aggregate qualified pipeline.
As a simple example, let’s imagine the qualification stage is a 40% probability, discovery moves it to 60%, proposing moves it to 80% and closing moves it to 90%. Then let’s further imagine we have $1M in opportunities in each stage. The forecast, based on this approach would be $2.7million. That’s the sum of the probability weighted opportunities at each stage.
Alternatively, we may say “Deal X has a forecast probability of 80% because it’s in the proposing stage.” And because the deal is a $2M deal, we commit $1.6M to the forecast. And our competitor on that deal, using the same standard CRM probabilities would commit $1.6M to the forecast, because it’s at an 80% probability. And the second competitor is doing the same thing.
So based on the most common methodology I see in committing things to the forecast, we and the other two competitors are going to our respective managers committing $1.6 m to our forecasts. But in the end, only one will win, and what they will win will be $2M, not the $1.6 committed to the forecast. And the other 2 will get $0, not the $1.6 each committed in their respective forecasts.
You can begin to see the problem. The logic of committing something to the forecast based on a stage based probability is nonsense–both if you win or lose. But the majority of forecasting methods are based on this flawed logic.
Whatever we think, whatever we wish or “fingers crossed” hope for is absolutely meaningless for a forecast.
The most important thing for a forecast is customer commitment. Are they going to make a decision to buy this quarter? While a simple question, it’s one that too many sellers don’t explore as deeply as they should with buyers, and the absence of this, diminishes the value we create and our probability of winning. So let’s dive into this for a moment, then come back to the forecast.
Are they going to buy this quarter? The fundamental principle underlying this is “change urgency.” We typically look at this asking questions like, “what’s the cost/risk of doing nothing, what’s the cost/risk of the change, is this the most important thing they must be doing?” These help us understand that they will make the change and when.
Then the next issue is, “will they select us to help them with the change?” Typically, we assess these by looking at mutual commitments made with the customer. Additionally, we can factor in past experience with that customer, the type of sale (e.g. net new, renewal, retention). We can also look at how we have fared in other similar situations.
The final issue is, “can the customer, with our support, complete all the work necessary in this timeframe?”
With each of these–will they buy, will they select us, can they complete the work; we can assess a risks based on the elements discussed. Then from these we can provide a weighted forecast. While it will seldom be 100% accurate, the basis for determining the weighting is based on more meaningful data driven by the customer.
When we start looking at commitment/urgency to change by the date the customer has established, and will they choose us, we now can start shifting our deal execution strategies and how we work with the customer to achieve these goals. We can work with them in looking at and managing where deals get stuck, where priorities might shift, where they may not have the right sponsorship or shared urgency in the organization, where there may be linked dependencies or conflicts in making the decision. We can work with them on the FOMU and related issues that might result in no decision made. Our actions become very focused and purposeful in working with the customer in achieving a shared goal.
And through doing this, we profoundly increase the likelihood of their choosing us. We are building trust and confidence, we are helping them learn and navigate their buying process. We are aligned in our mutual success.
In the end we seek to influence and manage three key commitments: change, execution, and vendor commitment. But all from the point of view of the customer and not through arbitrary stage gates in our sales process.
And we see something else. We shift from forecasting as a reporting exercise. Or forecasting to establish a number in the report. Now forecasting can help us focus our opportunity strategies, management, and execution.
Afterword: Here is an outstanding AI based conversation of this post. Enjoy!
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